This application addresses broad Challenge Area (10) Information Technology for Processing Health Care Data and specific Challenge Topic, 10-HD-101: Monitoring Rehabilitation Outcomes Many patients leave the acute care hospital to receive post-acute care (PAC) in another setting such as inpatient rehabilitation hospitals (IRF) and skilled nursing facilities (SNF). PAC is a health sector characterized by extremely rapid growth in providers, beneficiaries, use, and spending. For example, Medicare spending for inpatient rehabilitation facilities (IRF) services is projected to be $5.8 billion annually in 2009, and Medicare actuaries projected $22.8 billion in spending in 2008 at skilled nursing facilities (SNF). These two PAC settings are used by millions of patients, but until now there has been no way to compare their treatment outcomes. Because of the recent increase in PAC expenditures policymakers have called for the systematic investigation of the most effective and efficient settings to provide PAC services. This imperative requires the ability to track a patient's recovery throughout an entire episode of PAC, regardless of setting. Researchers at Boston University (BU) developed such an instrument, the Activity Measure for Post- Acute Care (AM-PAC) which can be used with patients recovering from many kinds of conditions, at many PAC sites. In 2007, researchers at BU collaborated with clinicians at Kaiser Permanente Northern California (KPNC) to install a computer version of AM-PAC, the AM-PAC CAT. The AM-PAC CAT uses Computer Assisted Technology (CAT) to assess rehabilitation treatment outcomes. The AM-PAC CAT can be integrated with an electronic medical record (EMR) to provide a single, integrated functional outcome measurement system. The AM-PAC CAT can be delivered through the same network, connected with the EMR, which offers the healthcare industry an ideal technical solution to to track rehabilitation outcomes and assure care effectiveness across PAC settings. The EMR used by KPNC tracks health information for 3.5 million members. While the AM-PAC CAT has been used to follow patients at many care settings in the KPNC system, KPNC would benefit from integrating AM-PAC CAT with the EMR so that the outcomes data can be combined with a patient's medical information.. This project proposes to integrate the AM-PAC CAT with the KPNC EMR This would result in the development of the Kaiser Permanente Functional Outcomes System (KP-FOS), an innovative clinical functional outcome system that can be used across all KPNC acute and PAC settings to monitor patient outcomes. . There are two components of this project. The first component is to integrate the AM-PAC CAT with the EMR, and develop a custom menu of functional outcome score (FOS) reporting options. The new reports will facilitate interpretation and use of functional status and clinical change information for clinicians, clinical researchers and program coordinators. The second component is testing the new KP-FOS with stroke patients. The data from the KP-FOS will be used to compare outcomes of patients who follow many different PAC pathways, particularly IRF and SNF. The success of this novel approach can serve as a model for other health systems to track patients with stroke and many other conditions throughout the continuum of care. KP- FOS can make possible a major transformation in the methods used in the evaluation and monitoring of clinical outcomes across care settings. When stroke patients leave the acute hospital they travel care paths through various post-acute care sites such as inpatient rehabilitation hospital, skilled nursing facility or home health. However their families and providers do not have a way to assess their care as they move from site to site. This project will extend and integrate with the Kaiser Permanente electronic medical record (EMR) a new functional outcomes assessment that is delivered by computer. Clinicians and computer programmers will design reports that integrate assessment scores with patient data from the EMR. Investigators will use the computerized assessment to measure rehabilitation outcomes for 244 stroke patients, following them for six months post-stroke and measuring their rehabilitation outcomes at each care site. The assessment scores will be integrated with patient data from the electronic medical record and analyzed using the new reports. This new approach to measuring rehabilitation outcomes will provide for the first time to patients and providers a tool to assess the appropriateness of care pathways factoring in individual patient data.